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Related Experiment Video

Updated: Oct 20, 2025

Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality
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P300 Brain-Computer Interface-Based Drone Control in Virtual and Augmented Reality.

Soram Kim1, Seungyun Lee1, Hyunsuk Kang1

  • 1School of Computer Science and Electrical Engineering, Handong Global University, Pohang 37554, Korea.

Sensors (Basel, Switzerland)
|September 10, 2021
PubMed
Summary
This summary is machine-generated.

This study developed a versatile brain-computer interface (BCI) application for virtual reality (VR) and augmented reality (AR). Findings show comparable BCI performance and user experience across both VR and AR environments.

Keywords:
BCI applicationP300augmented reality (AR)brain–computer interface (BCI)droneelectroencephalogram (EEG)virtual reality (VR)

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Area of Science:

  • Neuroscience
  • Human-Computer Interaction
  • Virtual and Augmented Reality

Background:

  • Head-mounted displays (HMDs) have spurred interest in integrating virtual reality (VR) and augmented reality (AR) into brain-computer interface (BCI) research.
  • A gap exists in studies directly comparing BCI performance between VR and AR environments.

Purpose of the Study:

  • To develop an open-source BCI application enabling comparative studies in both VR and AR.
  • To evaluate the performance and user experience of a P300-based BCI for drone control in VR versus AR.

Main Methods:

  • Developed an open-source drone control application utilizing a P300-based BCI, compatible with both VR and AR.
  • Recruited 20 healthy participants to operate the drone in both VR and AR environments.
  • Administered pre- and post-experiment questionnaires to assess user experience and collected online performance metrics.

Main Results:

  • No significant differences (p > 0.05) were observed in online BCI performance, including classification accuracy and P300 component characteristics (amplitude/latency), between VR and AR.
  • User experience metrics, encompassing satisfaction with duration, program, environment, interest, difficulty, immersion, and self-control, were also comparable across both immersive conditions.

Conclusions:

  • The P300-based BCI paradigm demonstrates reliability and effectiveness in both VR and AR settings.
  • The developed BCI application facilitates direct comparison of performance and user experience across different immersive realities, supporting future BCI research.